def add_salt_pepper(tomo, prob=0.01, val=None):
"""
Add salt and pepper noise.
Parameters
----------
tomo : ndarray
3D tomographic data.
prob : float, optional
Independent probability that each element of a pixel might be
corrupted by the salt and pepper type noise.
val : float, optional
Value to be assigned to the corrupted pixels.
Returns
-------
ndarray
3D tomographic data after salt and pepper noise added.
"""
tomo = dtype.as_ndarray(tomo)
dx, dy, dz = tomo.shape
ind = np.random.rand(dx, dy, dz) < prob
if val is None:
val = tomo.max()
tomo[ind] = val
return tomo
def add_salt_pepper(tomo, prob=0.01, val=None):
"""
Add salt and pepper noise.
Parameters
----------
tomo : ndarray
3D tomographic data.
prob : float, optional
Independent probability that each element of a pixel might be
corrupted by the salt and pepper type noise.
val : float, optional
Value to be assigned to the corrupted pixels.
Returns
-------
ndarray
3D tomographic data after salt and pepper noise added.
"""
tomo = dtype.as_ndarray(tomo)
dx, dy, dz = tomo.shape
ind = np.random.rand(dx, dy, dz) < prob
if val is None:
val = tomo.max()
tomo[ind] = val
return tomo
def add_gaussian(tomo, mean=0, std=None):
"""
Add Gaussian noise.
Parameters
----------
tomo : ndarray
3D tomographic data.
mean : float, optional
Mean of the Gaussian distribution.
std : float, optional
Standard deviation of the Gaussian distribution.
Returns
-------
ndarray
3D tomographic data after Gaussian noise added.
"""
tomo = dtype.as_ndarray(tomo)
if std is None:
std = tomo.max() * 0.05
dx, dy, dz = tomo.shape
tomo += std * np.random.randn(dx, dy, dz) + mean
return tomo
def add_gaussian(tomo, mean=0, std=None):
"""
Add Gaussian noise.
Parameters
----------
tomo : ndarray
3D tomographic data.
mean : float, optional
Mean of the Gaussian distribution.
std : float, optional
Standard deviation of the Gaussian distribution.
Returns
-------
ndarray
3D tomographic data after Gaussian noise added.
"""
tomo = dtype.as_ndarray(tomo)
if std is None:
std = tomo.max() * 0.05
dx, dy, dz = tomo.shape
tomo += std * np.random.randn(dx, dy, dz) + mean
return tomo
